Tumors and lesions are types of pathological anatomies characterized by abnormal growth of tissue resulting from the uncontrolled, progressive multiplication of cells, while serving no physiological function.
A non-invasive method for pathological anatomy treatment is external beam radiation therapy. In one type of external beam radiation therapy, an external radiation source is used to direct a sequence of x-ray beams at a tumor site from multiple angles, with the patient positioned so the tumor is at the center of rotation (isocenter) of the beam. As the angle of the radiation source is changed, every beam passes through the tumor site, but passes through a different area of healthy tissue on its way to the tumor. As a result, the cumulative radiation dose at the tumor is high and the average radiation dose to healthy tissue is low. The term radiotherapy refers to a procedure in which radiation is applied to a target region for therapeutic, rather than necrotic, purposes. The amount of radiation utilized in radiotherapy treatment sessions is typically about an order of magnitude smaller, as compared to the amount used in a radiosurgery session. Radiotherapy is typically characterized by a low dose per treatment (e.g., 100-200 centi-Grays (cGy)), short treatment times (e.g., 10 to 30 minutes per treatment) and hyperfractionation (e.g., 30 to 45 days of treatment). For convenience, the term “radiation treatment” is used herein to mean radiosurgery and/or radiotherapy unless otherwise noted by the magnitude of the radiation.
Conventional isocentered radiosurgery systems (e.g., the Gamma Knife) use forward treatment planning. That is, a medical physicist determines the radiation dose to be applied to a tumor and then calculates how much radiation will be absorbed by critical structures and other healthy tissue. There is no independent control of the two dose levels, for a given number of beams, because the volumetric energy density at any given distance from the isocenter is a constant, no matter where the isocenter is located.
Inverse planning, in contrast to forward planning, allows the medical physicist to independently specify the minimum tumor dose and the maximum dose to other healthy tissues, and lets the treatment planning software select the direction, distance, and total number and energy of the beams. Conventional treatment planning software packages are designed to import 3-D images from a diagnostic imaging source, for example, computerized x-ray tomography (CT) scans. CT is able to provide an accurate three-dimensional model of a volume of interest (e.g., skull or other tumor bearing portion of the body) generated from a collection of CT slices and, thereby, the volume requiring treatment can be visualized in three dimensions.
During inverse planning, a volume of interest (VOI) is used to delineate structures to be targeted or avoided with respect to the administered radiation dose. That is, the radiation source is positioned in a sequence calculated to localize the radiation dose into a VOI that as closely as possible conforms to the tumor requiring treatment, while avoiding exposure of nearby healthy tissue. Once the target (e.g., tumor) VOI has been defined, and the critical and soft tissue volumes have been specified, the responsible radiation oncologist or medical physicist specifies the minimum radiation dose to the target VOI and the maximum dose to normal and critical healthy tissue. The software then produces the inverse treatment plan, relying on the positional capabilities of the radiation treatment system, to meet the min/max dose constraints of the treatment plan.
The two principal requirements for an effective radiation treatment system are conformality and homogeneity. Homogeneity is the uniformity of the radiation dose over the volume of the target (e.g., pathological anatomy such as a tumor, lesion, vascular malformation, etc.) characterized by a dose volume histogram (DVH). An ideal DVH would be a rectangular function, where the dose is 100 percent of the prescribed dose over the volume of the tumor and zero elsewhere.
Conformality is the degree to which the radiation dose matches (conforms) to the shape and extent of the target (e.g., tumor) in order to avoid damage to critical adjacent structures. More specifically, conformality is a measure of the amount of prescription (Rx) dose (amount of dose applied) within a target VOI. Conformality may be measured using a conformality index (CI)=total volume at >=Rx dose/target volume at >=Rx dose. Perfect conformality results in a CI=1. With conventional radiotherapy treatment, using treatment planning software, a clinician identifies a dose isocontour for a corresponding VOI for application of a treatment dose (e.g., 2000 cGy).
FIG. 1 illustrates the graphical output of treatment planning software displaying a slice of a CT image a containing pathological anatomy (e.g., tumor, lesion, etc.) region and normal anatomy as a critical region (e.g., internal organ) to be avoided by radiation. The treatment planning software enables the generation of a critical region contour, a target (i.e., pathological anatomy) region contour, and a dose isocontour on the displayed CT slice. Conventionally, a user manually delineates points (e.g., some of the dots on the contour lines of FIG. 1) on the display that is used by the treatment planning software to generate the corresponding contours. While this may seem an easy task, such matching is difficult due to the 3 dimensional nature and irregularities of the pathological and normal anatomies.
Another problem with conventional planning methods is that it may be difficult to achieve the best possible conformality when relying solely on anatomical images on which to base dose constraints because these images provide no information related to current understandings of lesions at the molecular and chemical level. Advances in imaging now offer other types of image modalities to include “functional” information about a lesion, such as biological and mechanistic data. For example, positron emission tomography (PET) images can provide metabolic information about a pathological anatomy such as a lesion. Functional magnetic resonance imaging (fMRI) visualizes changes in the chemical composition of brain areas or changes in the flow of fluids. In PET images, the brightness of different areas of the image may be related to cell density. That is, the greater the brightness in a particular region, the higher the density of lesion cells in that region. It may then be desirable to deliver higher doses of radiation to certain regions of the lesion based on the functional image data. However, some conventional external beam radiation systems may not be able to deliver radiation dose accurately enough to discriminate among such regions within a lesion or tumor, thereby making such identifications unnecessary.
Moreover, despite advances in functional imaging and radiation dose delivery, an operator or physician must go through a number of tedious and time consuming steps to optimize a treatment plan based on combining functional image data with anatomical image data. For example, the physician would have to visually compare a CT image and a PET image of the same VOI, and determine which region of the CT image corresponds to a region of high lesion cell density shown on the PET image based on a visual inspection of different areas of brightness on the PET image. After this determination is made, the physician then would have to manually delineate the visually identified area of greater brightness (that may correspond to a region of high cell density). This process may have to be performed for multiple slices of the CT scan, making the planning process very laborious and time consuming. Moreover, such a manual process that involves the visual inspection of a PET image by a person may cause inaccuracies due to its subjective nature and the fallibility of the observing person.